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thinking-orbs

Add accessible animated AI loading and agent-status indicators with the React thinking-orbs library. Use when a chat, copilot, voice, search, generation, or tool-running interface needs a semantic working, searching, solving, listening, composing, or shaping state; when replacing a generic spinner with an AI activity orb; or when implementing the library's size, theme, speed, pause, reduced-motion, and canvas behavior.

72

Quality

87%

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SKILL.md
Quality
Evals
Security

Quality

Content

82%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-structured, actionable skill body with complete code examples and a strong verification checklist. Tightening the minor redundancy between the Core Contract and detail sections, and optionally splitting the advanced canvas API into a reference file, would raise it further.

Suggestions

Deduplicate guidance repeated between the Core Contract and the Choose the Size / Speed and Pause sections so each rule lives in one place.

Consider moving the Power-User Canvas API and STATE_TO_MODE mapping into a references/ file referenced from SKILL.md to deepen progressive disclosure for the advanced material.

Add an explicit validate→fix→retry note in the Verification section (e.g., on typecheck or build failure) to close the feedback-loop gap.

DimensionReasoningScore

Conciseness

Efficient and almost entirely library-specific (six states, sizes 20/64, theme resolution, runtime behaviors) with no generic concept padding; minor redundancy between the Core Contract and later sections (size and pause are restated) keeps it just below fully lean.

4 / 5

Actionability

Multiple complete, copy-paste-ready TSX/TS examples cover the common cases — Basic Usage, lifecycle mapping, accessible announcement, theme, speed/pause, Next.js client boundary, and the raw canvas API — all executable rather than pseudocode.

5 / 5

Workflow Clarity

A clear install-to-usage sequence plus a thorough 9-step Verification checklist with explicit confirmations; it lacks an explicit validate→fix→retry feedback loop, though the operation is non-destructive so the cap does not apply.

4 / 5

Progressive Disclosure

Well-organized with clear section headers and no bundle files to reference; the Power-User Canvas API and full runtime-behavior list are advanced content that could plausibly live in a separate reference file, but keeping them inline is reasonable for a focused single-library skill.

4 / 5

Total

17

/

20

Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A dense, well-constructed description that clearly states both capability and trigger conditions with library-specific detail. Minor additional synonyms would push trigger quality to full marks.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — "Add accessible animated AI loading and agent-status indicators", "replacing a generic spinner", and "implementing the library's size, theme, speed, pause, reduced-motion, and canvas behavior" — giving comprehensive coverage rather than just naming the domain.

5 / 5

Completeness

Explicitly states the what ("Add accessible animated AI loading and agent-status indicators with the React thinking-orbs library") and a detailed when with concrete trigger phrases ("Use when a chat, copilot, voice, search... interface needs a semantic... state").

5 / 5

Trigger Term Quality

Strong natural keyword coverage across interface types ("chat, copilot, voice, search, generation, or tool-running"), states ("working, searching, solving, listening, composing, or shaping"), and "generic spinner", but a few common phrasings like "loading spinner" or "AI status indicator" are absent, keeping it just short of comprehensive.

4 / 5

Distinctiveness Conflict Risk

Scoped to the specific "React thinking-orbs library" with distinctive triggers (AI activity orbs, six semantic states), giving it a clear niche with minimal overlap against generic loader skills.

5 / 5

Total

19

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
MengTo/Skills
Reviewed

Table of Contents

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